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11. Contemporary Management of Severe Symptomatic Aortic Stenosis

Author

Iung, Bernard, Bax, Jeroen, De Bonis, Michele, Delgado, Victoria, Haude, Michael, Hindricks, Gerhard, Maggioni, Aldo P., Pierard, Luc, Popescu, Bogdan A., Prendergast, Bernard, Price, Susanna, Rosenhek, Raphael, Ruschitzka, Frank, Vahanian, Alec, Wendler, Olaf, Windecker, Stephan, Mekhaldi, Souad, Lemaitre, Katell, Authier, Sébastien, Laroche, Cécile, Abdelhamid, Magdy, Apor, Astrid, Bajraktari, Gani, Beleslin, Branko, Bogachev-Prokophiev, Alexander, Demarco, Daniela Cassar, Pasquet, Agnes, Dogan, Sait Mesut, Erglis, Andrejs, Evangelista, Arturo, Goda, Artan, Ihlemann, Nikolaj, Ince, Huseyin, Katsaros, Andreas, Linhartova, Katerina, Mascherbauer, Julia, Mirrakhimov, Erkin, Mizariene, Vaida, Rahman-Haley, Shelley, Ribeiras, Regina, Samadov, Fuad, Saraste, Antti, Simkova, Iveta, Kostovska, Elizabeta Srbinovska, Tomkiewicz-Pajak, Lidia, Tribouilloy, Christophe, Zera, Eliverta, Metalla, Mimoza, Shirka, Ervina, Dado, Elona, Bica, Loreta, Aleksi, Jorida, Knuti, Gerti, Gjyli, Lidra, Pjeci, Rudina, Shuperka, Eritinka, Lleshi, Erviola, Rustemaj, Joana, Qordja, Marsjon, Gina, Mirald, Husi, Senada, Basic, Daniel, Steringer-Mascherbauer, Regina, Huber, Charlotte, Ebner, Christian, Sigmund, Elisabeth, Ploechl, Andrea, Sturmberger, Thomas, Eder, Veronica, Koppler, Tanja, Heger, Maria, Kammerlander, Andreas, Duca, Franz, Binder, Christina, Koschutnik, Matthias, Perschy, Leonard, Puskas, Lisa, Ho, Chen-Yu, Aliyev, Farid, Guluzada, Vugar, Imanov, Galib, Ibrahimov, Firdovsi, Abbasaliyev, Abbasali, Ahmedov, Tahir, Muslumova, Fargana, Babayev, Jamil, Rustamova, Yasmin, Jahangirov, Tofig, Samadov, Rauf, Museyibov, Muxtar, Isayev, Elnur, Musayev, Oktay, Xalilov, Shahin, Huseynov, Saleh, Yuzbashova, Madina, Zamanov, Vuqar, Mammadov, Vusal, Van Camp, Gery, Penicka, Martin, Batjoens, Hedwig, Debonnaire, Philippe, Dendooven, Daniel, Knecht, Sebastien, Duytschaever, Mattias, Vandekerckhove, Yves, Missault, Luc, Muyldermans, Luc, Tavernier, René, De Grande, Tineke, Coussement, Patrick, DeTroyer, Joyce, Derycker, Katrien, De Jaegher, Kelly, Bondue, Antoine, Beauloye, Christophe, Goffinet, Céline, Mirica, Daniela Corina, Eynden, Frédéric Vanden, Van de Borne, Philippe, Van Frachen, Béatrice, Vancraeynest, David, Vanoverschelde, Jean Louis, Pierard, Sophie, Malanca, Mihaela, Sinnaeve, Florence, Tahon, Séverine, De Clippel, Marie, Gayet, Frederic, Loiseau, Jacques, Van de Veire, Nico, Moerman, Veronique, Willems, Anne-Marie, Cosyns, Bernard, Droogmans, Steven, Motoc, Andreea, Kerkhove, Dirk, Plein, Daniele, Roosens, Bram, Weytjens, Caroline, Lancellotti, Patrizio, Dulgheru, Elena Raluca, Parenicova, Ilona, Bedanova, Helena, Tousek, Frantisek, Sindelarova, Stepanka, Canadyova, Julia, Taborsky, Milos, Ostransky, Jiri, Ivona simkova, Vicha, Marek, Jelinek, Libor, Opavska, Irena, Homza, Miroslav, Kvrayola, Miriam, Brat, Radim, Mrozek, Dan, Lichnerova, Eva, Docekalova, Iveta, Zarybnicka, Marta, Peskova, Marketa, Roucka, Patrik, Stastna, Vlasta, Vondrackova, Dagmar Jungwirtova, Hornig, Alfred, Niznansky, Matus, Branny, Marian, Vodzinska, Alexandra, Dorda, Miloslav, Snkouril, Libor, Kluz, Krystyna, Kypusova, Jana, Nezvalova, Radka, Olsen, Niels Thue, Ali, Hosam Hasan, Taha, Salma, Hassan, Mohamed, Afifi, Ahmed, Kabil, Hamza, Mady, Amr, Ebaid, Hany, Ahmed, Yasser, Nour, Mohammad, Talaat, Islam, Sayed, CairoMaiy El, Mostafa, Ahmad Elsayed, Sadek, CairoYasser, Eltobgi, CairoSherif, Bakhoum, Sameh, Doss, Ramy, Sheashea, Mahmoud, Elasry, Abd Allah, Fouad, Ahmed, Baraka, Mahmoud, Samir, Sameh, Roshdy, Alaa, AbdelRazek, Yasmin, Abd Rabou, Mostafa M., Abobakr, Ahmed, Moaaz, Moemen, Mokhtar, Mohamed, Ashry, Mohamed, Elkhashab, Khaled, Ghareeb, Haytham Soliman, Kamal, Mostafa, AbdelRazek, Gomaa, Farag, GizaNabil, Elbarbary, Giza:Ahmed, Wahib, Evette, Kazamel, Ghada, Kamal, Diaa, Tantawy, Mahmoud, Alansary, Adel, Yahia, Mohammed, Mahmoud, Raouf, El Banna, Tamer, Atef, Mohamed, Nasr, Gamela, Ahmed, Salah, El Hefny, Ehab E., Saifelyazal, Islam, El Ghany, Mostafa Abd, El Rahman El Hadary, Abd, Khairy, Ahmed, Lommi, Jyri, Laine, Mika, Kylmala, Minna, Kankanen, Katja, Turpeinen, Anu, Hartikainen, Juha, Kujanen, Lari, Airaksinen, Juhani, Vasankari, Tuija, Szymanski, Catherine, Bohbot, Yohann, Gun, Mesut, Rousseaux, Justine, Biere, Loic, Mateus, Victor, Audonnet, Martin, Rautureau, Jérémy, Cornet, Charles, Sorbets, Emmanuel, Mear, BourgesKarine, Issa, Adi, Jobic, Yannick, Le Ven, Florent, Pouliquen, Marie-Claire, Gilard, Martine, Ohanessian, Alice, Farhat, Ali, Vlase, Alina, Said, Fkhar, Lasgi, Caroline, Sanchez, Carlos, Breil, Romain, Peignon, Marc, Elkaim, Jean-Philippe, Jan-Blin, Virginie, BertrandM'Ban, Sylvain Ropars, Bardet, Hélène, Sawadogo, Samuel, Muschoot, Aurélie, Tchatchoua, Dieudonné, Elhadad, Simon, Maubert, Aline, Lazizi, Tahar, Ourghi, Kais, Bonnet, Philippe, Menager-Gangloff, Clarisse, Gafsi, Sofiene, Mansouri, Djidjiga, Aboyans, Victor, Magne, Julien, Martins, Elie, Karm, Sarah, Mohty, Dania, Briday, Guillaume, David, Amandine, Marechaux, Sylvestre, Le Goffic, Caroline, Binda, Camille, Menet, Aymeric, Delelis, Francois, Ringlé, Anne, Castel, Anne-Laure, Appert, Ludovic, Tristram, Domitille, Trouillet, Camille, Nacer, Yasmine, Ngoy, Lucas, Habib, MarseilleGilbert, Thuny, Franck, Haentjens, Julie, Cautela, Jennifer, Lavoute, Cécile, Robin, Floriane, Armangau, Pauline, Vergeylen, Ugo, Sanhadji, Khalil, Abdallah, Nessim Hamed, Kerzazi, Hassan, Perianu, Mariana, Plurien, François, Oueslati, Chaker, Debauchez, Mathieu, Monin, Jean-Luc, Konstantinos, Zannis, Berrebi, Alain, Dibie, Alain, Lansac, Emmanuel, Veugeois, Aurélie, Diakov, Christelle, Caussin, Christophe, Czitrom, Daniel, Salvi, Suzanna, Amabile, Nicolas, Dervanian, Patrice, Lejeune, Stéphanie, Bagdadi, Imane, Mokrane, Yemmi, Rouault, Gilles, Abalea, Jerome, Leledy, Marion, Horen, Patrice, Donal, Erwan, Bosseau, Christian, Paven, Elise, Galli, Elena, Collette, Edouard, Urien, Jean-Marie, Bridonneau, Valentin, Gervais, Renaud, Bauer, Fabrice, Chopra, Houzefa, Charbonnier, Arthur, Attias, David, Dahouathi, Nesrine, Khounlaboud, Moukda, Daudin, Magalie, Thebault, Christophe, Hamon, Cécile, Couffon, Philippe, Bellot, Catherine, Vomscheid, Maelle, Bernard, Anne, Dion, Fanny, Naudin, Djedjiga, Mouzouri, Mohammed, Rudelin, Mathilde, Berenfeld, Alain, Vanzwaelmen, Thibault, Alloui, Tarik, Radovikj, Marija Gjerakaroska, Jordanova, Slavica, Scholtz, Werner, Liberda-Knoke, Eva, Wiemer, Melanie, Mugge, Andreas, Nickenig, Georg, Sinning, Jan-Malte, Sedaghat, Alexander, Heintzen, Matthias, Ballof, Jan, Frenk, Daniel, Hambrecht, Rainer, Wienbergen, Harm, Seidel, Annemarie, Osteresch, Rico, Kramer, Kirsten, Ziemann, Janna, Schulze, Ramona, Fehske, Wolfgang, Eifler, Clarissa, Wafaisade, Bahram, Kuhn, Andreas, Fischer, Sören, Lichtenberg, Lutz, Brunold, Mareike, Simons, Judith, Balling, Doris, Buck, Thomas, Plicht, Bjoern, Schols, Wolfgang, Ebelt, Henning, Chamieh, Marwan, Anacker, Jelena, Rassaf, Tienush, Janosi, Alexander, Lind, Alexander, Lortz, Julia, Lüdike, Peter, Kahlert, Philipp, Rittger, Harald, Eichinger, Gabriele, Kuhls, Britta, Felix, Stephan B., Lehnert, Kristin, Pedersen, Ann-Louise, Dorr, Marcus, Empen, Klaus, Kaczmarek, Sabine, Busch, Mathias, Baly, Mohammed, Er, Fikret, Duman, Erkan, Gabriel, Linda, Weinbrenner, Christof, Bauersachs, Johann, Wider, Julian, Kempf, Tibor, Bohm, Michael, Schulze, Paul-Christian, Poerner, C. Tudor, Möbius-Winkler, Sven, Lenk, Karsten, Heitkamp, Kerstin, Franz, Marcus, Krauspe, Sabine, Schumacher, Burghard, Windmuller, Volker, Kurwitz, Sarah, Thiele, Holger, Kurz, Thomas, Meyer-Saraei, Roza, Akin, Ibrahim, Fastner, Christian, Lossnitzer, Dirk, Hoffmann, Ursula, Borggrefe, Martin, Baumann, Stefan, Kircher, Brigitte, Foellinger, Claudia, Dietz, Heike, Schieffer, Bernhard, Niroomand, Feraydoon, Mudra, Harald, Maier, Lars, Camboni, Daniele, Birner, Christoph, Debl, Kurt, Paulus, Michael, Seither, Benedikt, El Mokhtari, Nour Eddine, Oner, Alper, Caglayan, Evren, Sherif, Mohammed, Yucel, Seyrani, Custodis, Florian, Schwinger, Robert, Vorpahl, Marc, Seyfarth, Melchior, Nover, Ina, Koehler, Till, Christiani, Sarah, Sanchez, David Calvo, Schanze, Barbel, Sigusch, Holger, Salman, Athir, Hancock, Jane, Chambers, John, Demetrescue, Camelia, Prendergast, Claire, Dalby, Miles, Smith, Robert, Rogers, Paula, Riley, Cheryl, Tousoulis, Dimitris, Kanakakis, Ioannis, Spargias, Konstantinos, Lampropoulos, Konstantinos, Panagiotis, Tolis, Koutsoukis, Athanasios, Michalis, Lampros, Goudevenos, Ioannis, Bellos, Vasileios, Papafaklis, Michail, Lakkas, Lampros, Hahalis, George, Makris, Athanasios, Karvounis, Haralampos, Kamperidis, Vasileios, Ninios, Vlasis, Sachpekidis, Vasileios, Rouskas, Pavlos, Poulimenos, Leonidas, Charalampidis, Georgios, Hamodraka, Eftihia, Manolis, Athanasios, Kiss, Robert Gabor, Borsanyi, Tunde, Jarai, Zoltan, Zsary, Andras, Bartha, Elektra, Kosztin, Annamaria, Doronina, Alexandra, Kovacs, Attila, Imre, Barabas Janos, Chao, Chun, Benke, Kalman, Karoczkai, Istvan, Keltai, Kati, Förchécz, Zsolt, Pozsonyi, Zoltán, Jenei, Zsigmond, Patthy, Adam, Sallai, Laszlo, Majoros, Zsuzsanna, Pál, Tamás, Bencze, Jusztina, Sagi, Ildiko, Molnar, Andrea, Kurczina, Anita, Kolodzey, Gabor, Edes, Istvan, Szatmari, Valeria, Zajacz, Zsuzsanna, Cziraki, Attila, Nemeth, Adam, Faludi, Reka, Vegh, Laszlone, Jebelovszki, Eva, Lupkovics, Geza Karoly, Kovacs, Zsofia, Horvath, Andras, Berisha, Gezim, Ibrahimi, Pranvera, Percuku, Luan, Arapova, Rano, Laahunova, Elmira, Neronova, Kseniia, Zhakypova, Zarema, Naizabekova, Gulira, Muratova, Gulnazik, Sime, Iveta, Sorokins, Nikolajs, Kamzola, Ginta, Cgojeva-Sproge, Irina, Rancane, Gita, Valentinaviciene, Ramune, Rudiene, Laima, Raugaliene, Rasa, Bardzilauske, Aiste, Jonkaitiene, Regina, Petrauskaite, Jurate, Bieseviciene, Monika, Verseckaite, Raimonda, Zvirblyte, Ruta, Kalibatiene, Danute, Radauskaite, Greta, Janaviciute-Matuzeviciene, Gabija, Jancauskaite, Dovile, Balkute, Deimile, Maneikyte, Juste, Mileryte, Ingrida, Vaisvilaite, Monika, Gedvilaite, Lina, Biliukas, Mykolas, Karpaviciene, Vaiva, Xuereb, Robert George, Pllaha, Elton, Djaberi, Roxana, Komor, Klaudiusz, Gorgon-Komor, Agnieszka, Loranc, Beata, Myszor, Jaroslaw, Mizia-Stec, Katarzyna, Berger-Kucza, Adrianna, Mizia, Magdalena, Polak, Mateusz, Bogacki, Piotr, Podolec, Piotr, Komar, Monika, Sedziwy, Ewa, Sliwiak, Dorota, Sobien, Bartosz, Rog, Beata, Hlawaty, Marta, Gancarczyk, Urszula, Libiszewska, Natasza, Sorysz, Danuta, Gackowski, Andrzej, Cieply, Malgorzata, Misiuda, Agnieszka, Racibor, Franciszek, Nytko, Anna, Widenka, Kazimierz, Kolowca, Maciej, Bak, Janusz, Curzytek, Andrzej, Regulski, Mateusz, Kamela, Malgorzata, Wisniowski, Mateusz, Hryniewiecki, Tomasz, Szymanski, Piotr, Rozewicz, Monika, Grabowski, Maciej, Duchnowski, Piotr, Budaj, Andrzej, Zaborska, Beata, Pilichowska-Paskiet, Ewa, Sikora-Frac, Malgorzata, Slomski, Tomasz, Joao, Isabel, Cruz, Ines, Pereira, Hélder, Cale, Rita, Marques, Ana, Pereira, Ana Rita, Morais, Carlos, Freitas, Antonio, Roque, David, Antunes, Nuno, Pereira, Antonio Costeira, Vieira, Catarina, Salome, Nuno, Martins, Juliana, Campos, Isabel, Cardoso, Goncalo, Silva, Claudia, Oliveira, Afonso, Goncalves, Mariana, Martins, Rui, Quintal, Nuno, Mendes, Bruno, Silva, Joseline, Ferreira, Joao, Milner, James, Alves, Patricia, Marinho, Vera, Gago, Paula, Amado, Jose, Bispo, Joao, Bento, Dina, Machado, Inocencia, Oliveira, Margarida, Calvo, Lucy, von Hate, Pedro, Faria, Bebiana, Galrinho, Ana, Branco, Luisa, Goncalves, Antonio, Mendonca, Tiago, Selas, Mafalda, Macedo, Filipe, Sousa, Carla, Cabral, Sofia, Oliveira, Filomena, Trepa, Maria, Fontes-Oliveira, Marta, Nunes, Alzira, Araújo, Paulo, Ribeiro, Vasco Gama, Almeida, Joao, Rodrigues, Alberto, Braga, Pedro, Dias, Sonia, Carvalho, Sofia, Ferreira, Catarina, Ferreira, Alberto, Mateus, Pedro, Moz, Miguel, Leao, Silvia, Margato, Renato, Moreira, Ilidio, Guimanaes, Jose, Ribeiro, Joana, Goncalves, Fernando, Cabral, Jose, Almeida, Ines, Goncalves, Luisa, Tarusi, Mariana, Pop, Calin, Matei, Claudia, Tint, Diana, Barbulescu, Sanziana, Micu, Sorin, Pop, Ioana, Baba, Costica, Dimulescu, Doina, Dorobantu, Maria, Ginghina, Carmen, Onut, Roxana, Popescu, Andreea, Zamfirescu, Brandusa, Aflorii, Raluca, Popescu, Mihaela, Ghilencea, Liviu, Rachieru, Andreeea, Stoian, Monica, Oprescu, Nicoleta, Iancovici, Silvia, Petre, Iona, Mateescu, Anca Doina, Calin, Andreea, Botezatu, Simona, Enache, Roxana, Rosca, Monica, Ciuperca, Daniela, Babalac, Evelyn, Beyer, Ruxandra, Cadis, Laura, Rancea, Raluca, Tomoaia, Raluca, Rosianu, Adela, Kovacs, Emese, Militaru, Constantin, Craciun, Alina, Mirea, Oana, Florescu, Mihaela, Grigorica, Lucica, Dragusin, Daniela, Nechita, Luiza, Marinescu, Mihai, Chiscaneanu, Teodor, Botezatu, Lucia, Corciova, Costela, Petris, Antoniu Octavian, Arsenescu-Georgescu, Catalina, Salaru, Delia, Alexandrescu, Dan Mihai, Plesoianu, Carmjen, Tanasa, Ana, Mitu, Ovidiu, Costache, Irina Iuliana, Tudorancea, Ionut, Usurelu, Catalin, Eminovici, Gabriela, Manitiu, Ioan, Stoia, Oana, Mitre, Adriana, Nistor, Dan-Octavian, Maier, Anca, Lupu, Silvia, Opris, Mihaela, Ionac, Adina, Popescu, Irina, Crisan, Simina, Mornos, Cristian, Goanta, Flavia, Gruescu, Liana, Voinescu, Oana, Petcu, Madalina, Cozlac, Ramona, Damrina, Elena, Khilova, Liliya, Ryazantseva, Irina, Kozmin, Dmitry, Kiseleva, Maria, Goncharova, Marina, Kitalaeva, Kamila, Demetskay, Victoria, Verevetinov, Artem, Fomenko, Mikhail, Skripkina, Elena, Tsoi, Viktor, Antipov, Georgii, Schneider, Yuri, Yazikov, Denis, Makarova, Marina, Cherkes, Aleksei, Ermakova, Natalya, Medvedev, Aleksandr, Sarosek, Anastasia, Isayan, Mikhail, Voronova, Tatyana, Kulumbegov, Oleg, Tuchina, Alina, Stefanov, Sergei, Klimova, Margarita, Smolyaninov, Konstantin, Dandarova, Zhargalma, Magamet, Victoriya, Spiropulos, Natalia, Boldyrev, Sergey, Barbukhatty, Kirill, Buyankov, Dmitrii, Yurin, Vladimir, Gross, Yuriy, Boronin, Maksim, Mikhaleva, Mariya, Shablovskaya, Mariya, Zotov, Alex, Borisov, Daniil, Tereshchenko, Vasily, Zubova, Ekaterina, Kuzmin, A., Tarasenko, Ivan, Gamzaev, Alishir, Borovkova, Natalya, Koroleva, Tatyana, Botova, Svetlana, Pochinka, Ilya, Dunaeva, Vera, Teplitskaya, Victoria, Semenova, Elena I., Korabel'Nikova, Olga V., Simonov, Denis S., Denisenko, Elena, Harina, Natalia, Yarohno, Natalia, Alekseeva, Svetlana, Abydenkova, Julia, Shabalkina, Lyubov, Mayorova, Olga, Tsechanovich, Valeriy, Medvedev, Igor, Lepilin, Michail, Nemchenko, PenzaEvgenii, Karnahin, Vadim, Safina, Vasilya, Slastin, Yaroslav, Gilfanova, Venera, Gorbunov, Roman, Jakubov, Ramis, Fazylova, Aigul, Poteev, Mansur, Vazetdinova, Laysan, Tarasova, Indira, Irgaliyev, Rishat, Moiseeva, Olga, Gordeev, Mikhail, Irtyuga, Olga, Moiseeva, Raisa, Ostanina, Nina, Zverev, Dmitry, Murtazalieva, Patimat, Kuznetsov, Dmitry, Skurativa, Mariya, Polyaeva, Larisa, Mihaiilov, Kirill, Obrenovic-Kircanski, Biljana, Putnik, Svetozar, Simic, Dragan, Petrovic, Milan, Nikolic, Natasa Markovic, Jovovic, Ljiljana, Ostric, Dimitra Kalimanovska, Brajovic, Milan, Manojlovic, Milica Dekleva, Novakovic, Vladimir, Zamaklar-Trifunovic, Danijela, Orbovic, Bojana, Petrovic, Olga, Boricic-Kostic, Marija, Andjelkovic, Kristina, Milanov, Marko, Despotovic-Nikolic, Maja, Budisavljevic, Sreten, Veljkovic, Sanja, Cvetinovic, Nataša, Lepojevic, Daniijela, Todorovic, Aleksandra, Nikolic, Aleksandra, Borzanovic, Branislava, Trkulja, Ljiljana, Tomic, Slobodan, Vukovic, Milan, Milosavljevic, Jelica, Milanovic, Mirjana, Stakic, Vladan, Cvetkovic, Aleksandra, Milutinovic, Suzana, Bozic, Olivera, Miladinovic, Miodrag, Nikolic, Zoran, Despotovic, Dinka, Jovanovic, Dimitrije, Stojsic-Milosavljevic, Anastazija, Ilic, Aleksandra, Sladojevic, Mirjana, Susak, Stamenko, Maletin, Srdjan, Pavlovic, Salvo, Kuzmanovic, Vladimir, Ivanovic, Nikola, Dejanovic, Jovana, Ruzicic, Dusan, Drajic, Dragana, Cvetanovic, Danijel, Mirkovic, Marija, Omoran, Jon, Margoczy, Roman, Sedminova, Katarina, Reptova, Adriana, Baranova, Eva, Valkovicova, Tatiana, Valocik, Gabriel, Kurecko, Marian, Vachalcova, Marianna, Kollarova, Alzbeta, Studencan, Martin, Alusik, Daniel, Kozlej, Marek, Macakova, Jana, Moral, Sergio, Cladellas, Merce, Luiso, Daniele, Calvo, Alicia, Palet, Jordi, Carballo, Juli, Tura, Gisela Teixido, Maldonado, Giuliana, Gutierrez, Laura, Gonzalez-Alujas, Teresa, Jose Fernando, Rodriguez Palomares, Villalva, Nicolas, Molina-Mora, Ma Jose, Paton, Ramon Rubio, Martinez Diaz, Juan Jose, Ruiz, Pablo Ramos, Valle, Alfonso, Rodriguez, Ana, Alania, Edgardo, Galcera, Emilio, Seller, Julia, Valenzuela, Gonzalo de la Morena, Espin, Daniel Saura, Garcia, Dolores Espinosa, Oliva Sandoval, Maria Jose, Gonzalez, Josefa, Navarro, Miguel Garcia, Perez-Martinez, Maria Teresa, Ortega Trujillo, Jose Ramon, Gallego, Irene Menduina, San Roman, Daniel, Perez Nogales, Eliu David, Medina, Olga, Montiel Quintero, Rodolfo Antonio, Bujanda Morun, Pablo Felipe, Perez, Marta Lopez, Huaripata, Jimmy Plasencia, Morales Gonzalez, Juan Jose, Nelson, Veronica Quevedo, Zamorano, Jose Luis, Gomez, Ariana Gonzalez, Fraile, Alfonso, Alberca, Maria Teresa, Martin, Joaquin Alonso, Fernandez-Golfin, Covadonga, Ramos, Javier, Jimenez, Sergio Hernandez, Mitroi, Cristina, Sanchez Fernandez, Pedro L., Diaz-Pelaez, Elena, Garde, Beatriz, Caballero, Luis, Garcia, Fermin Martinez, Cambronero, Francisco, Castro, Noelia, Castro, Antonio, De La Rosa, Alejandro, Gallego, Pastora, Mendez, Irene, Villegas, David Villagomez, Correa, Manuel Gonzalez, Calvo, Roman, Florian, Francisco, Paya, Rafael, Esteban, Esther, Buendia, Francisco, Cubillos, Andrés, Fernandez, Carmen, Cárdenas, Juan Pablo, Pérez-Boscá, José Leandro, Vano, Joan, Belchi, Joaquina, Iglesia-Carreno, Cristina, Iglesias, Francisco Calvo, Escudero-Gonzalez, Aida, Zapateria-Lucea, Sergio, Duarte, Juan Sterling, Perez-Davila, Lara, Cobas-Paz, Rafael, Besada-Montenegro, Rosario, Fontao-Romeo, Maribel, Lopez-Rodriguez, Elena, Paredes-Galan, Emilio, Caneiro-Queija, Berenice, Gonzalez, Alba Guitian, Bozkurt, Abdi, Demir, Serafettin, Unlu, Durmus, Cagliyan, Caglar Emre, Ikikardes, Muslum Firat, Tangalay, Mustafa, Kuloglu, Osman, Ozer, Necla, Canpolat, Ugur, Kemaloglu, Melek Didem, Demirtas, Abdullah Orhan, Akgün, Didar Elif, Avci, Eyup, Taylan, Gokay, Yilmaztepe, Mustafa Adem, Ucar, Fatih Mehmet, Altay, Servet, Gurdogan, Muhammet, Gudul, Naile Eris, Aktas, Mujdat, Buyuklu, Mutlu, Degirmenci, Husnu, Turan, Mehmet Salih, Mert, Kadir Ugur, Mert, Gurbet Ozge, Dural, Muhammet, Arslan, Sukru, Sayar, Nurten, Kanar, Batur, Sadic, Beste Ozben, Sahin, Ahmet Anil, Buyuk, Ahmet, Kilicarslan, Onur, Bostan, Cem, Yildirim, Tarik, Yildirim, Seda Elcim, Cosansu, Kahraman, Varim, Perihan, Ilguz, Ersin, Demirbag, Recep, Yesilay, Asuman, Cirit, Abdullah, Tusun, Eyyup, Erkus, Emre, Sayin, Muhammet Rasit, Kazaz, Zeynep, Kul, Selim, Karabag, Turgut, Kalayci, Belma, Eugène, Marc, and Bax, Jeroen J.

Published
2021
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19. The Relationship Between Endocan and Serum Inflammatory Markers in Patients with Senile Calcific Aortic Stenosis.

Author

Akgün, Didar Elif, Avcı, Eyüp, Yaman, Ali, Şafak, Özgen, Kısacık, Halil Lütfi, Argan, Onur, Yıldırım, Seda Elçim, Yıldırım, Tarık, Naser, Abdulrahman, Gençbay, Murat, and Kırış, Tuncay

Subjects
AORTIC stenosis, BIOMARKERS, CORONARY artery disease, AORTIC valve, AORTIC valve insufficiency, ATHEROSCLEROSIS
Abstract

Background: Endocan is an indicator of many pathologies accompanied by inflammation, endothelial cell activation, and dysfunction. In this study, we examined the relationship between degenerative aortic sclerosis, which progresses in a similar pathophysiologic mechanism as atherosclerosis, and serum inflammatory markers and endocan levels. Methods: A total of 155 patients without known coronary artery disease, aged between 65 and 80 years, were consecutively included in the prospective cross-sectional study. The study population was analyzed in 4 different groups. The control group consisted of patients with normal aortic valve structure, while patients with aortic stenosis were classified as mild aortic stenosis (2-2.9 m/s), moderate aortic stenosis (3-3.9 m/s), and severe aortic stenosis (= 4 m/s) according to their aortic velocity. While there were 39 patients in the control group, there were 58, 24, and 34 patients in the mild, moderate, and severe aortic stenosis groups, respectively. Results: There was no statistically significant difference between the groups in terms of patient distribution and characteristics. History of dyspnea and angina was correlated with the severity of aortic stenosis (P < .001). In this study, no statistically significant correlation was found between serum endocan levels and the severity of aortic stenosis (control group: 17.3 ± 6.3 ng/mL, mild aortic stenosis: 17.6 ± 8.7 ng/mL, moderate aortic stenosis: 16.3 ± 3.8 ng/mL, severe aortic stenosis: 15.2 ± 5.9 ng/mL, P = .396). However, it was figured out that there was a positive correlation between endocan levels and hemoglobin (Hg) (r = 0.308, P = .001), platelet (PLT) (r = 0.320, P < .001), and albumin (Alb) (r = 0.206, P = .026). Conclusion: In this study, no significant correlation was found between serum endocan levels and the severity of aortic stenosis. On the other hand, there was a positive correlation between endocan levels and Hg, PLT, and Alb. [ABSTRACT FROM AUTHOR]

Published
2024
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21. ON NEW GENERALIZED FRACTIONAL MIDPOINT-TYPE INEQUALITIES FOR CO-ORDINATED CONVEX AND CO-ORDINATED CONCAVE FUNCTIONS.

Author

Yıldırım, Seda Kılınç, Kara, Hasan, Budak, Hüseyin, and Yıldırım, Hüseyin

Subjects
*CONCAVE functions, *FRACTIONAL integrals, *DIFFERENTIABLE functions, *CONVEX functions
Abstract

In this paper, we firstly obtain a new generalized identity for twice partially differentiable functions Riemann-Liouville fractional integrals. Then, using this equality, we obtain some midpoint-type inequalities for co-ordinated convex and co-ordinated concave functions. We also show that our result generalizes the give several inequalities obtained in earlier works. [ABSTRACT FROM AUTHOR]

Published
2023
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22. Winner or loser? The asymmetric role of natural resource rents on financial development among resource‐rich countries.

Author

Yıldırım, Seda, Yıldırım, Durmuş Çağrı, Bostancı, Seda H., and Tarı, Elif Nur

Subjects
NATURAL resources, RESOURCE curse, RENT, COUNTRIES
Abstract

The resource curse theory has become a paradox that has been discussed for many years in the literature. Because most studies have revealed empirical evidence that resource rents negatively affect financial development although resource wealth provides many advantages. Therefore, studies on whether studies conducted with different methods in different periods can produce results contrary to this theory are continuing. This study aims to test the asymmetric effect of natural resource rents on financial development among resource‐rich countries. The study investigated the data of 10 countries those have the highest natural resource rents in the World that selected from World Atlas (2018) for the period 1993–2017. As a result of empirical analysis, this study proved that there was a financial resource curse hypothesis among resource‐rich countries. While positive shocks are effecting financial development negatively, negative shocks are found as effecting financial development positively. This study also showed that resource‐rich countries are lucky but not a winner in the context of financial development and sustainable development. [ABSTRACT FROM AUTHOR]

Published
2022
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23. COVID-19 pandemisinin sağlık yönetimi ve sağlık hizmetleri üzerine etkisi: Türkiye örneği]

Author

Öncü, Mehmet Akif, Yıldırım, Seda, Bostancı, Seda Hilmiye, and Erdoğan, Fatma

Subjects
health care organization, health care personnel, pandemic, public health, COVID-19 pandemic, health care cost, mobile application, Health policy, Health services, Article, developed country, Turkey (republic), coronavirus disease 2019, Health management, health care policy, health insurance, life expectancy, health care management, human, health service, qualitative research
Abstract

Aim: The coronavirus disease 2019 (COVID-19) pandemic is a global issue that every country has begun to change its economic and social policies due to sustaining public health in the long term. The aim of this study is to investigate the effects of the COVID-19 pandemic on health management and health services in Turkey. Material and Methods: This study follows a qualitative research methodology and used secondary data sources. The study used open access data based on The Turkish Statistical Institute (TurkStat) and the Republic of Turkey Ministry of Health. Data were analyzed by Qualitative Content Analysis. Results: According to the findings obtained, the study provides two main parts as findings. First, the study presents a current profile for the Turkish health sector including 2010-2019. Secondly, the study provides key elements indicating the effect of the COVID-19 pandemic on health management and health services in Turkey. With the help of classification, tables, and figures, the study provides original findings for the area of health management by giving what kinds of changes have occurred in health policies during COVID-19. Conclusion: When considering the effect of the COVID-19 pandemic on health management and health services in Turkey, it can be said that Turkey has managed this pandemic period sufficiently. As a sample case, Turkish health policies and new management strategies can guide other developing and developed countries that were unsuccessful to manage the COVID-19 pandemic. This study shows that adaptable and sustainable health policies will keep public health in the long term. © 2021, Duzce University Medical School. All rights reserved.

Published
2021

24. Türkiye'de Katılım Bankalarının Müşteri Perspektifinden Performanslarının İncelenmesi: Kocaeli İli Örneği

Author

Erdoğan, Seyfettin, Gedikli, Ayfer, Yıldırım, Seda, Yıldırım, Durmuş Çağrı, Yılmaz Genç, Sema, Haykır Hobikoğlu, Elif, and Erdoğan, Fatma

Subjects
participation bank, Participation banking, Satisfaction, Awareness, Loyalty, Islamic Banking, Choice, Preferences, customer preferences, Service Quality, Products, Selection Criteria, Islamic Economy, Determinants
Abstract

To have an uninterrupted growth performance of participation banks may beonly possible by sustainable development strategies that are consistent withmarket dynamics. Investigating the reasons why customers prefer theseinstitutions, what their expectations are, and analyzing the data obtained fromthese researches are critical in developing strategies. Comprehensive fieldresearch covering all provinces of Turkey which aims to determine the reasonsfor customer preference of participation banks may provide policy implicationsfor the policymakers. As the first step towards carrying out such research, it wasaimed to investigate the reasons for preferring participation banks in Kocaeliprovince. In the study, the required data were collected and analyzed with thehelp of quantitative and qualitative research methods. Firstly, an in-depthinterview method was applied in qualitative research to obtain the data from 12customers working with participation banks in a long period of time. Secondly,the questionnaire method was used to collect data from a wider customer sampleregarding the factors that are important for working with the participationbanks. 407 questionnaires were analyzed and interpreted. 5 main factors, suchas religious factors, service quality variables, social environment effect, financial variables, and marketing mix variables were found to be effective in preferringparticipation banks. The findings of this exploratory study are consistent withthe related literature and it is expected to guide to future studies. Katılım bankalarının büyüme performansının belirli bir eşikten sonra sekteye uğramaması, sürdürülebilir ve piyasa dinamikleri ile tutarlı stratejilerin geliştirilmesi ile mümkün olabilir. Müşterilerin bu kurumları hangi gerekçeler ile tercih ettiği ve beklentilerinin neler olduğu konusunun araştırılması ve bu araştırmalardan elde edilen verilerin analiz edilmesi tutarlı stratejilerin geliştirilmesi açısından önem arz etmektedir. Türkiye genelinde yapılacak kapsamlı bir araştırma ile müşterilerin katılım bankalarını tercih etme gerekçeleri tespit edilerek geliştirilecek politika uygulamalarına dayanak oluşturulabilir. Böyle bir araştırmanın gerçekleştirilmesine yönelik bir adım olarak Kocaeli özelinde katılım bankalarının tercih edilme gerekçelerinin araştırılması amaçlanmıştır. Çalışmada nicel ve nitel araştırma yöntemleri yardımıyla gerekli veriler toplanarak, analiz edilmiştir. Öncelikle nitel araştırma kapsamında derinlemesine görüşme yönteminden yararlanılarak uzun süreli katılım bankaları ile çalışan 12 müşteriden gerekli bilgiler elde edilmiştir. İkinci olarak, anket yöntemi ile daha geniş bir müşteri örneğinden katılım bankalarının tercih edilmesinde önemli olan faktörlere yönelik bilgiler toplanmıştır. 407 adet anket formu analiz edilerek, yorumlanmış ve dini faktörler, hizmet kalitesi ile ilgili değişkenler, sosyal çevre etkisi, finansal değişkenler ve pazarlama karması ile ilgili değişkenler şeklinde 5 temel faktörün katılım bankası tercihinde etkili olduğu görülmüştür. Keşifsel bir araştırma özelliği taşıyan bu çalışmanın bulguları, literatür ile uyumlu sonuçlar vermekte olup, gelecek çalışmalara yol göstereceği düşünülmektedir.

Published
2020

26. Işık Üniversitesi final sınav programı için genetik algoritma uygulaması

Author

Yıldırım, Seda, Atan, Sabri Tankut, Işık Üniversitesi, Fen Bilimleri Enstitüsü, Endüstri Mühendisliği Yüksek Lisans Programı, Işık Üniversitesi, Fen Bilimleri Enstitüsü, Endüstri Mühendisliği - Yöneylem Araştırması Yüksek Lisans Programı, and Yıldırım, Seda

Subjects
Tamsayılı doğrusal programlama, Research, Industrial -- Turkey, Industrial engineering -- Mathematical models, Genetik algoritma, Integer linear model, Memetic algorithm, Genetic algorithms, Memetik algoritma, Mathematical optimization, Genetic algorithm, Industrial engineering, Sınav çizelgelemesi, Exam timetabling, T56.42 .Y55 2013, Technology assessment -- Turkey
Abstract

Text in English ; Abstract: English and Turkish Includes bibliographical references (leaves 32-34) x, 64 leaves Exam timetabling is a widely encountered scheduling problem at educational institutions. Typically, exam timetabling problems involve some hard constraints and several soft constraints that may vary from one institution to another. One of the soft constraints is that as few students as possible should have more than a predefined number of exams on the same day. At Isik University, if students have more than two exams on the same day they are allowed to ask for makeup exams for the extra exams. While integer programming formulations with other constraints of Isik University could be solved to optimality via commercial solvers, incorporating the daily exam limitation rule proved to be intractable. Hence a genetic algorithm was developed. Using data from several semesters, numerical experiments were conducted to tune the developed genetic algorithm's parameters and test it. The new metaheuristic algorithm was also coded in Java programming language and integrated into finexa, the internally developed exam timetabling software at Isik University. Üniversitelerde sık ça kar şılaşı lan çizelgeleme problemlerden biri sı nav haftası programın ın ayarlanmas ıd ır. S ınav saatleri ayarlan ırken zorunlu ve zorunlu olmayan k ısı tlar g öz ön ünde bulundurulur. Zorunlu olmayan k ıs ıtlardan biri, aynı g ünde istenilenden daha fazla sınava girecek olan ö ğrenci say ısı nı n olabildi ğince az olması kı s ıt ıd ır. I şı k Üniversitesinde bir g ünde ikiden fazla finali olan öğrenciler mazeret s ınavı na girebilme hakkı na sahiptir. I şık Üniversitesinde final program ı ayarlanı rken dikkat edilen di ğer kurallar i çin tamsayı lı programlama ile çöz üm üretilebilirken bahsedilen k ıs ıt problemi bu y öntemle çöz ülemez hale getirdi. Bu nedenle yakla şık bir y öntem ile çöz üm üretme zorunlulu ğu do ğdu. Geli ştirilen genetik algoritmayı test ederken d ört d önemin verisinden faydaland ık. Ayr ıca yeni y öntem Java dilinde kodlanarak I şık Üniversitesinde kullanı lan s ınav çizelgeleme programı nexa aray üz üne entegre edildi. Introduction Motivation Related Work Outline of Thesis Integer Programming Formulations Final Exam Scheduling at Işık University Core Model Index sets Parameters Decision variables Formulation Model With No 3 Exam Rule Index sets Parameters Decision variables Formulation Genetic Algorithm (GA) and Exam Scheduling GA Initialization Evaluation Selection Recombination Mutation Replacement GA for Exam Scheduling Construction Heuristic Improvement Algorithm Solution Representation Crossover and Mutation Operators Experiments Problem Instances Preliminary Experiments Memetic Algorithm Conclusion

Published
2013

28. Comparison of Cardiac Autonomic Functions in Glucometabolic Disturbances.

Author

Yıldırım, Seda Elçim, Yıldırım, Tarık, and Özçelik, Fatih

Subjects
*NEUROPATHY, *DIABETES complications, *HEART beat
Abstract

Introduction: Autonomic neuropathy is a common complication of diabetes mellitus. The aim of the present study was to compare heart rate recovery time and heart rate variation among the indicators of cardiac autonomic function between patients with glucometabolic abnormalities in various levels and normal glucose homeostasis. Methods: A total of 90 patients were enrolled in the study. The patients were divided into four groups: impaired fasting glucose (IFG) (n=18), impaired glucose tolerance (IGT) (n=25), type 2 diabetes mellitus (DM) (n=21), and the control group (n=26). Cardiac autonomic neuropathy (CAN) was evaluated by the maximum exercise stress test and Holter electrocardiography. Results: The baseline heart rate in the DM group was higher than the IFG, IGT, and control groups, but the difference was not statistically significant (93.5±15.5, 87.8±9.4, 84.3±10.8, and 84.3±14.2, respectively; p=0.06). In multiple regression analysis FPG level was an independent variable, increased baseline heart rate was correlated with an elevated FPG level (constant: 71.35, p: 0.004). The metabolic equivalent of task (MET) value was lower in the DM group compared to the IFG, IGT, and control groups (9.9±1.2, 9.0±1.6, 9.78±1.46, 8.77±1.74 p=0.06). Conclusion: When compared to patients with normal glucose homeostasis heart rate at rest was higher in the IGT, IFG, and DM groups. Elevated fasting glucose levels were correlated with an increased baseline heart rate. A negative correlation was found between HbA1c levels and HRRT, and HR index. These finding indicate autonomic functions are impaired in patients with DM, IGT and IFG groups. [ABSTRACT FROM AUTHOR]

Published
2016

29. SEGMENTATION OF FEMALE APPAREL MARKET THROUGH CONSUMER DECISION-MAKING STYLES.

Author

Yıldırım, Seda, Aydın, Kenan, and Ustaahmetoğlu, Erol

Subjects
*MARKET segmentation, *CONSUMER behavior, *WOMEN'S clothing
Abstract

The market of women apparel is in a quite growing trend todays. So this big market has a great competition and businesses try to catch customer and get customer loyalty. But businesses should know how women make buying decision for fashion apparel products and what kinds of specific characteristics defines women in fashion apparel market. In this concept, consumer decision-making style inventory(CSI) of Kendall and Splores(1986) has been an useful tool for both businesses and academics to understand consumer's buying behavior and so determining specific sub-markets in related markets or sectors. With this study, it was purposed to determine women's decision-making styles in apparel products and get a significant sub-segments for apparel market. A survey method was used and this survey included the scale of Consumer Style Inventory(CSI) with 40-items were adapted for apparel products. Then this survey was implemented to females that visiting a big shopping mall that called as Outlet Center which was thought as one of biggest shopping areas in Kocaeli,Turkey. From distributed 500 survey forms, 390 of them was collected as suitable for analyses. Results of analyses showed that females could be segmented through consumer decision-making styles as perfect-brand lovers, hedonist-fashion keepers, confused-impulsive buyers and price keepers in female apparel market. [ABSTRACT FROM AUTHOR]

Published
2016

31. Time-Varying Convergences of Environmental Footprint Levels between European Countries.

Author

Yıldırım, Durmuş Çağrı, Yıldırım, Seda, Erdoğan, Seyfettin, Demirtaş, Işıl, Couto, Gualter, Castanho, Rui Alexandre, and Boland, John

Subjects
*ECOLOGICAL impact, *COUNTRIES, *GOVERNMENT policy, *FOOT movements, *ACCOUNTING methods
Abstract

This study proposes the time-varying nonlinear panel unit root test to investigate the convergence of ecological foot prints between the EU and candidate countries. Sixteen European countries (such as Albania, Austria, Belgium, Denmark, France, Germany, Greece, Italy, Luxembourg, Netherlands, Poland, Portugal, Romania, Spain, Sweden and Turkey) and analysis periods are selected according to data availability. This study proposes a cross-sectional Panel KSS with Fourier to test the convergence of the ecological footprints. Then, we combine this methodology with the rolling window method to take into account the time-varying stationarity of series. This study evaluated sub-components of ecological footprints separately and provided more comprehensive findings for the ecological footprint. According to empirical findings, this study proves that convergence or divergence does not show continuity over time. On the other side, this study points out the presence of divergence draws attention when considering the properties of the sub-components in general. As a result, this study shows that international policies by EU countries are generally accepted as successful to reduce ecological footprint, but these are not sufficient as expected. In this point, it is suggested to keep national policies to support international policies in the long term. [ABSTRACT FROM AUTHOR]

Published
2021
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33. The protective role of curcumin on perfluorooctane sulfonate-induced genotoxicity: Single cell gel electrophoresis and micronucleus test

Author

Çelik, Ayla, Eke, Dilek, Ekinci, Seda Yaprak, and Yıldırım, Seda

Subjects
*CURCUMIN, *PERFLUOROOCTANE sulfonate, *GENETIC toxicology, *GEL electrophoresis, *NUCLEOLUS, *POLLUTANTS, *BIOACCUMULATION, *POLYPHENOLS
Abstract

Abstract: Perfluorooctane sulfonate (PFOS) is a man-made fluorosurfactant and global pollutant. PFOS a persistent and bioaccumulative compound, is widely distributed in humans and wildlife. Therefore, it was added to Annex B of the Stockholm Convention on Persistent Organic Pollutants in May 2009. Curcumin is a natural polyphenolic compound abundant in the rhizome of the perennial herb turmeric. It is commonly used as a dietary spice and coloring agent in cooking and anecdotally as an herb in traditional Asian medicine. In this study, male rats were treated with three different PFOS doses (0.6, 1.25 and 2.5mg/kg) and one dose of curcumin, from Curcuma longa (80mg/kg) and combined three doses of PFOS with 80mg/kg dose of curcumin by gavage for 30days at 48h intervals. Here, we evaluated the DNA damage via single cell gel electrophoresis or comet assay and micronucleus test in bone marrow in vivo. PFOS induced micronucleus frequency and decreased the ratio of polychromatic erythrocyte to normochromatic erythrocyte in bone marrow. Using the alkaline comet assay, we showed that all doses of the PFOS strongly induced DNA damage in rat bone marrow and curcumin prevented the formation of DNA damage induced by PFOS. [Copyright &y& Elsevier]

Published
2013
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34. Case Image: An unusual cause of dyspnea: Spontaneous pneumopericardium.

Author

Yıldırım T, Altun İ, Yıldırım SE, Akın F, and Soylu MÖ

Subjects
Bronchial Fistula complications, Bronchial Fistula diagnostic imaging, Diagnosis, Differential, Dyspnea etiology, Fatal Outcome, Humans, Male, Middle Aged, Pericardium diagnostic imaging, Pericardium pathology, Pneumopericardium complications, Pneumopericardium diagnostic imaging, Tomography, X-Ray Computed, Bronchial Fistula diagnosis, Lung Neoplasms, Pneumopericardium diagnosis
Published
2018
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